What outcomes should be evaluated in critically ill patients?

Family Satisfaction With Critical Care: Before and After the COVID-19 Outbreak

Introduction Family satisfaction with intensive care units (ICU) is recognized as a key component of the quality of care. As a result, family members are now more involved in the care process, and their needs are recognized throughout the ICU stay. The coronavirus disease 2019 (COVID-19) changed healthcare worldwide, due to the several restrictions imposed; the communication patterns changed drastically, and institutions were forced to adapt to create a balance between security and the needs of relatives. The aim of this study was to assess family members' satisfaction with the ICU and determine if the COVID-19 restructuring affected family satisfaction. Methods A prospective observational study was performed among the designated family members (DFM) of ICU patients over two time periods, a pre-pandemic period from December 2019 to February 2020 and a pandemic period from May 2020 to February 2021. The Family Satisfaction in the Intensive Care Unit 24 (FS-ICU 24) questionnaire, which was given to the DFM, was the instrument used to determine family satisfaction. Results The study involved 290 DFM, 175 during the pre-pandemic phase and 115 during the pandemic period. The overall and domain-specific family satisfaction scores were high (score > 80) in both the pre-pandemic and pandemic periods. The greatest satisfaction levels were related with symptom management and how nurses and doctors cared for the patient. No statistical differences were found between the two time periods. Lastly, a positive association between the two domains explored by FS-ICU 24, satisfaction with care and satisfaction with decision-making process, was verified in both time frames. Conclusion The data obtained revealed very good outcomes on the different FS-ICU 24 domains, in line with other studies in literature. No significant differences were found between the pre-pandemic and pandemic periods, suggesting that the measures implemented during the COVID-19 were successful. The importance of involving families in the decision-making process, providing them with accurate information, and active listening, as well as using better communication skills, is emphasized throughout all these results. The relevance of measuring family satisfaction should be brought to the attention of family members and healthcare professionals so that additional research may be conducted.

Impact of Energy and Protein Delivery to Critically Ill Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Optimal energy and protein delivery goals for critically ill patients remain unknown. The purpose of this systematic review and meta-analysis was to compare the impact of energy and protein delivery during the first 4 to 10 days of an ICU stay on physical impairments. We performed a systematic literature search of MEDLINE, CENTRAL, and ICHUSHI to identify randomized controlled trials (RCTs) that compared energy delivery at a cut-off of 20 kcal/kg/day or 70% of estimated energy expenditure or protein delivery at 1 g/kg/day achieved within 4 to 10 days after admission to the ICU. The primary outcome was activities of daily living (ADL). Secondary outcomes were physical functions, changes in muscle mass, quality of life, mortality, length of hospital stay, and adverse events. Fifteen RCTs on energy delivery and 14 on protein were included in the analysis. No significant differences were observed in any of the outcomes included for energy delivery. However, regarding protein delivery, there was a slight improvement in ADL (odds ratio 21.55, 95% confidence interval (CI) −1.30 to 44.40, p = 0.06) and significantly attenuated muscle loss (mean difference 0.47, 95% CI 0.24 to 0.71, p < 0.0001). Limited numbers of RCTs were available to analyze the effects of physical impairments. In contrast to energy delivery, protein delivery ≥1 g/kg/day achieved within 4 to 10 days after admission to the ICU significantly attenuated muscle loss and slightly improved ADL in critically ill patients. Further RCTs are needed to investigate their effects on physical impairments.

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Intensive care unit (ICU) patients with venous thromboembolism (VTE) and/or cancer suffer from high mortality rates. Mortality prediction in the ICU has been a major medical challenge for which several scoring systems exist but lack in specificity. This study focuses on two target groups, namely patients with thrombosis or cancer. The main goal is to develop and validate interpretable machine learning (ML) models to predict early and late mortality, while exploiting all available data stored in the medical record. To this end, retrospective data from two freely accessible databases, MIMIC-III and eICU, were used. Well-established ML algorithms were implemented utilizing automated and purposely built ML frameworks for addressing class imbalance. Prediction of early mortality showed excellent performance in both disease categories, in terms of the area under the receiver operating characteristic curve (AUC–ROC): VTE-MIMIC-III 0.93, eICU 0.87, cancer-MIMIC-III 0.94. On the other hand, late mortality prediction showed lower performance, i.e., AUC–ROC: VTE 0.82, cancer 0.74–0.88. The predictive model of early mortality developed from 1651 VTE patients (MIMIC-III) ended up with a signature of 35 features and was externally validated in 2659 patients from the eICU dataset. Our model outperformed traditional scoring systems in predicting early as well as late mortality. Novel biomarkers, such as red cell distribution width, were identified.